Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes well beyond the annotations: cost (USD 0.005), free tier (5 calls/IP/UTC day), character cap, latency expectations (4-10 s for 200 chars, ~1 min for 2,000), and mapped error codes (422 bad input, 503 busy, 504 timeout, none charged). It also discloses data handling — submitted text not logged, results retained only for the url option — which the annotations' readOnlyHint=false/openWorldHint=true cannot convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose and the sibling call-out, then limits, then cost/latency, then data handling — a sensible ordering with no wasted lead-in. There is minor redundancy ("41 voices" and the 6-language list appear twice, and the docs URL is a tail append), but every distinct operational fact earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With five parameters, an output schema already present, and 100% schema coverage, the description supplies exactly the missing operational layer: cost, quota, timeouts, size cap, latency, and retention. Nothing an agent needs in order to call this correctly or to decide between base64 and url is absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the per-parameter meanings are already documented; the description still adds value by explaining the voice/language coupling (the voice dictates the language, so text must match it) and the practical consequence of `output` (save data_base64 to a file, or get a 24 h link). It stops short of adding anything new on speed or format beyond what the schema says.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Speak text aloud") with the concrete scope of 41 voices across 6 named languages and the offline Kokoro-82M engine. It explicitly distinguishes itself from the audio-to-text sibling by naming transcribe_audio, so an agent can route without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Names the inverse tool explicitly ("For audio to text use transcribe_audio") and gives concrete decision criteria for the output parameter (inline base64 vs. 24 h url). It also tells the caller to write the text in the voice's language, which is a real usage prerequisite rather than a restatement.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.